On the TeraGrid, what is Big Ben?

On the TeraGrid, Big Ben (tg-login.bigben.psc.teragrid.org) is the Cray XT3 system at Pittsburgh Supercomputing Center (PSC).

Big Ben is configured with 2,068 compute nodes linked by a custom-designed interconnect. Twenty-two dedicated I/O processors are also connected to this network. Each compute node has two 2.6GHz AMD Opteron processors. Each compute processor has its own cache, but the two processors on a node share 2GB of memory and the network connection.

Each compute processor runs the Catamount operating system. Catamount is a subset of Unix, and consequently not all Unix system calls are available on the compute processors. For example, you cannot use threads on Big Ben's compute processors, therefore OpenMP is not available on Big Ben. However, typical computational science applications do not rely on system calls and hence should easily port to Big Ben. To ask if a particular Unix call is supported on Catamount, email  remarks@psc.edu .

There are multiple front-end processors (also AMD Opterons) running SuSE Linux. Logins are to one of these front-end processors, not to the compute processors.

Big Ben is primarily intended to run applications with very high levels of parallelism or concurrency (using between 512 and 4,136 processors). To apply for a production or a development grant on Big Ben, fill out the POPS proposal form.

For user documentation, see the Big Ben home page.

Note: This is a TeraGrid Roaming resource. See the TeraGrid User Support documentation for a dynamically generated list of all Roaming resources.

As part of the transition to TeraGrid XD, this resource will be decommissioned in the near future. For decommission dates of retiring TeraGrid systems, see the XD Transition page on the TeraGrid web site.

For further information about compute and visualization resources on the TeraGrid, see the Resource Catalog in the TeraGrid User Support documentation.

This document was developed with support from the National Science Foundation (NSF) under Grant No. 0503697 to the University of Chicago and subcontracted to Indiana University. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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